We are now in an era of an FDA approved prophylactic HPV16/18 vaccine for the two major types of HPV causing cervix cancer. Nevertheless, there are many critical questions about the natural history of non-HPV16/18 HPV types associated with cervix cancer and the fine specificity of the vaccine that remain and need to be addressed. The central hypothesis of this application is that DNA mutation and natural selection have driven the evolution of success amongst HPV infections resulting also in the emergence of cancer causing viruses, as a byproduct of filling a specific biological niche. We will utilize epidemiological methods and the analytic tools of evolution and systems biology to study the role of oncogenic HPV types and variants in population-based studies of HPV natural history and cervix neoplasia. We propose 3 specific aims: (1) To define the natural history of the a7 (18-related) and a9 (16-related) HPV types in the HPV Persistence and Progression (PaP) Cohort at Kaiser Permanente Northern California, a new cohort study of 35,000 HR-HPV positive (HC2+) women z 30 yrs of age women and in the 21,000 women from the Portland study with 16 years of follow-up; (2) To determine vaccine efficacy for HPV16/18-variants and related type variants after vaccination with HPV16/18 VLPs in the Costa Rica Vaccine Trial (CVT), a phase III HPV 16/18 vaccine trial of 7500 women 18-25 years of age in Guanacaste; and (3) To identify the genetic basis for the oncogenicity of high-risk HPV types and variants. There is a gradient of oncogenic risk from the most oncogenic, HPV16, to less oncogenic types (e.g., HPV31/35/45/56) to non-oncogenic (e.g., HPV53/70) HPV types within the oncogenic species groups a.5-7, a9 and a11. We will infer full viral genome sequence from variant haplotype information. This data will be combined with pathologic state and/or case-control status from the results generated in the cohort studies to determine genotype-phenotype relationships using a variety of phylogenetic and analytic approaches. Overall the data will provide important information on phenotypic-genetic relationships.